Data Engineer

About Raven Data

Raven Data specializes in digital human‑behavior analytics, helping organizations optimize performance and streamline business processes. Our multidisciplinary team combines deep research expertise with cutting‑edge technical skills in data engineering, analytics, and AI / ML.

Role Overview

As a Data Engineer at Raven Data, you will lead the entire data lifecycle—gathering and translating business requirements, ingesting and integrating diverse data sources, and designing, building, and orchestrating robust ETL/ELT pipelines with built‑in quality checks, governance, and observability. You’ll partner with data scientists to prepare, deploy, and monitor ML/AI models in production, and work closely with analysts and stakeholders to transform raw data into actionable insights and scalable intelligence.

What You’ll Do

E2E Solution Delivery:

Lead the full spectrum of data projects—requirements gathering, data ingestion, modeling, validation, and production deployment.

Data Modeling:

Develop and maintain robust logical and physical data models—such as star and snowflake schemas—to support analytics, reporting, and scalable data architectures.

Data Analysis & BI:

Transform complex datasets into clear, actionable insights; develop dashboards and reports that drive operational efficiency and revenue growth.

ML Engineering:

Implement and manage model‑serving pipelines using cloud’s MLOps toolchain, ensuring reliability and monitoring in production.

Collaboration & Research:

Partner with cross‑functional teams to prototype solutions, identify new opportunities, and drive continuous improvement.

What We’re Looking For

Experience: 2+ years in a data‑focused role (Data Engineer, BI Developer, or similar)

Technical Skills: Proficient in SQL and Python for data manipulation, cleaning, transformation, and ETL workflows. Strong understanding of statistical methods and data modeling concepts. Soft Skills: Excellent problem‑solving ability, critical thinking, and attention to detail. Outstanding written and verbal communication.

Education: BSc or higher in Mathematics, Statistics, Engineering, Computer Science, Life Science, or a related quantitative discipline.

Nice to Have

Cloud & Data Warehousing: Hands‑on experience with cloud platforms (GCP, AWS or others) and modern data warehouses such as BigQuery and Snowflake.